DOI10.1137/080731359zbMath1215.65108arXiv0807.4423OpenAlexW2117198760MaRDI QIDQ3083289
Pierre-Antoine Absil, Michel Journée, Francis Bach, Rodolphe J. Sepulchre
Publication date: 21 March 2011
Published in: SIAM Journal on Optimization (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0807.4423
Finding graph embeddings by incremental low-rank semidefinite programming,
Manifold Optimization-Assisted Gaussian Variational Approximation,
Unnamed Item,
Unnamed Item,
Fenchel Duality and a Separation Theorem on Hadamard Manifolds,
SpeeDP: an algorithm to compute SDP bounds for very large max-cut instances,
The geometry of algorithms using hierarchical tensors,
Solutions to 18 constrained optimization problems on the rank and inertia of the linear matrix function,
An alternative to EM for Gaussian mixture models: batch and stochastic Riemannian optimization,
A hierarchy of spectral relaxations for polynomial optimization,
Convergence Results for Projected Line-Search Methods on Varieties of Low-Rank Matrices Via Łojasiewicz Inequality,
Fast certifiable relative pose estimation with gravity prior,
Operator-valued formulas for Riemannian gradient and Hessian and families of tractable metrics in Riemannian optimization,
Normal Cones Intersection Rule and Optimality Analysis for Low-Rank Matrix Optimization with Affine Manifolds,
A Decomposition Augmented Lagrangian Method for Low-Rank Semidefinite Programming,
Time-Varying Semidefinite Programming: Path Following a Burer–Monteiro Factorization,
Solving PhaseLift by Low-Rank Riemannian Optimization Methods for Complex Semidefinite Constraints,
Restricted Riemannian geometry for positive semidefinite matrices,
A brief introduction to manifold optimization,
Approximation bounds for sparse principal component analysis,
Mini-workshop: Computational optimization on manifolds. Abstracts from the mini-workshop held November 15--21, 2020 (online meeting),
A survey on rank and inertia optimization problems of the matrix-valued function \(A+BXB^\ast\),
Mahalanobis Distance Learning for Person Re-identification,
Memory-Efficient Structured Convex Optimization via Extreme Point Sampling,
Accelerated method for optimization over density matrices in quantum state estimation,
Tightness of the maximum likelihood semidefinite relaxation for angular synchronization,
Nonconvex weak sharp minima on Riemannian manifolds,
Scalable incremental nonconvex optimization approach for phase retrieval,
A survey on conic relaxations of optimal power flow problem,
Riemannian Preconditioning,
Computational Approaches to Max-Cut,
Adaptive regularization with cubics on manifolds,
Flexible low-rank statistical modeling with missing data and side information,
On the Burer-Monteiro method for general semidefinite programs,
Scalable Low-Rank Semidefinite Programming for Certifiably Correct Machine Perception,
Quotient Geometry with Simple Geodesics for the Manifold of Fixed-Rank Positive-Semidefinite Matrices,
Matrix optimization over low-rank spectral sets: stationary points and local and global minimizers,
Rank Optimality for the Burer--Monteiro Factorization,
Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of Markov Chains,
Finding Low-Rank Solutions via Nonconvex Matrix Factorization, Efficiently and Provably,
On the Landscape of Synchronization Networks: A Perspective from Nonconvex Optimization,
Convergence rate of block-coordinate maximization Burer-Monteiro method for solving large SDPs,
Global Registration of Multiple Point Clouds Using Semidefinite Programming,
A Riemannian symmetric rank-one trust-region method,
Balanced Truncation for Parametric Linear Systems Using Interpolation of Gramians: A Comparison of Algebraic and Geometric Approaches,
Unnamed Item,
Unnamed Item,
Low-rank multi-parametric covariance identification,
Exact Worst-Case Performance of First-Order Methods for Composite Convex Optimization